toggle visibility Search & Display Options

Select All    Deselect All
 |   | 
Details
   print
  Records Links
Author KM3NeT Collaboration (Aiello, S. et al); Alves Garre, S.; Calvo, D.; Carretero, V.; Colomer, M.; Corredoira, I; Gozzini, S.R.; Hernandez-Rey, J.J.; Illuminati, G.; Khan Chowdhury, N.R.; Manczak, J.; Pieterse, C.; Real, D.; Salesa Greus, F.; Thakore, T.; Zornoza, J.D.; Zuñiga, J. url  doi
openurl 
  Title (down) gSeaGen: The KM3NeT GENIE-based code for neutrino telescopes Type Journal Article
  Year 2020 Publication Computer Physics Communications Abbreviated Journal Comput. Phys. Commun.  
  Volume 256 Issue Pages 107477 - 15pp  
  Keywords Astroparticle physics; High energy neutrinos; Monte Carlo event generator; Neutrino telescopes; Neutrino oscillations; KM3NeT; GENIE  
  Abstract The gSeaGen code is a GENIE-based application developed to efficiently generate high statistics samples of events, induced by neutrino interactions, detectable in a neutrino telescope. The gSeaGen code is able to generate events induced by all neutrino flavours, considering topological differences between tracktype and shower-like events. Neutrino interactions are simulated taking into account the density and the composition of the media surrounding the detector. The main features of gSeaGen are presented together with some examples of its application within the KM3NeT project. Program summary Program Title: gSeaGen CPC Library link to program files: http://dx.doi.org/10.17632/ymgxvy2br4.1 Licensing provisions: GPLv3 Programming language: C++ External routines/libraries: GENIE [1] and its external dependencies. Linkable to MUSIC [2] and PROPOSAL [3]. Nature of problem: Development of a code to generate detectable events in neutrino telescopes, using modern and maintained neutrino interaction simulation libraries which include the state-of-the-art physics models. The default application is the simulation of neutrino interactions within KM3NeT [4]. Solution method: Neutrino interactions are simulated using GENIE, a modern framework for Monte Carlo event generators. The GENIE framework, used by nearly all modern neutrino experiments, is considered as a reference code within the neutrino community. Additional comments including restrictions and unusual features: The code was tested with GENIE version 2.12.10 and it is linkable with release series 3. Presently valid up to 5 TeV. This limitation is not intrinsic to the code but due to the present GENIE valid energy range. References: [1] C. Andreopoulos at al., Nucl. Instrum. Meth. A614 (2010) 87. [2] P. Antonioli et al., Astropart. Phys. 7 (1997) 357. [3] J. H. Koehne et al., Comput. Phys. Commun. 184 (2013) 2070. [4] S. Adrian-Martinez et al., J. Phys. G: Nucl. Part. Phys. 43 (2016) 084001.  
  Address [Aiello, S.; Leonora, E.; Longhitano, F.; Randazzo, N.] Ist Nazl Fis Nucl, Sez Catania, Via Santa Sofia 64, I-95123 Catania, Italy, Email: distefano_c@lns.infn.it  
  Corporate Author Thesis  
  Publisher Elsevier Place of Publication Editor  
  Language English Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 0010-4655 ISBN Medium  
  Area Expedition Conference  
  Notes WOS:000564482200008 Approved no  
  Is ISI yes International Collaboration yes  
  Call Number IFIC @ pastor @ Serial 4520  
Permanent link to this record
 

 
Author Perez-Calatayud, J.; Ballester, F.; Tedgren, C.; DeWerd, L.A.; Papagiannis, P.; Rivard, M.J.; Siebert, F.A.; Vijande, J. doi  openurl
  Title (down) GEC-ESTRO ACROP recommendations on calibration and traceability of HE HDR-PDR photon-emitting brachytherapy sources at the hospital level Type Journal Article
  Year 2022 Publication Radiotherapy and Oncology Abbreviated Journal Radiother. Oncol.  
  Volume 176 Issue Pages 108-117  
  Keywords Brachytherapy; High energy; Calibration; Dosimetry; HDR-PDR  
  Abstract The vast majority of radiotherapy departments in Europe using brachytherapy (BT) perform temporary implants of high-or pulsed-dose rate (HDR-PDR) sources with photon energies higher than 50 keV. Such techniques are successfully applied to diverse pathologies and clinical scenarios. These recommen-dations are the result of Working Package 21 (WP-21) initiated within the BRAchytherapy PHYsics Quality Assurance System (BRAPHYQS) GEC-ESTRO working group with a focus on HDR-PDR source cal-ibration. They provide guidance on the calibration of such sources, including practical aspects and issues not specifically accounted for in well-accepted societal recommendations, complementing the BRAPHYQS WP-18 Report dedicated to low energy BT photon emitting sources (seeds). The aim of this report is to provide a European-wide standard in HDR-PDR BT source calibration at the hospital level to maintain high quality patient treatments.  
  Address [Perez-Calatayud, Jose] La Fe Hosp, Radiotherapy Dept, Valencia, Spain, Email: javier.vijande@uv.es  
  Corporate Author Thesis  
  Publisher Elsevier Ireland Ltd Place of Publication Editor  
  Language English Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 0167-8140 ISBN Medium  
  Area Expedition Conference  
  Notes WOS:000880438000006 Approved no  
  Is ISI yes International Collaboration yes  
  Call Number IFIC @ pastor @ Serial 5466  
Permanent link to this record
 

 
Author HAWC Collaboration (Alfaro, R. et al); Salesa Greus, F. url  doi
openurl 
  Title (down) Gamma/hadron separation with the HAWC observatory Type Journal Article
  Year 2022 Publication Nuclear Instruments & Methods in Physics Research A Abbreviated Journal Nucl. Instrum. Methods Phys. Res. A  
  Volume 1039 Issue Pages 166984 - 13pp  
  Keywords High energy; Crab Nebula; G/H separation; Machine Learning  
  Abstract The High Altitude Water Cherenkov (HAWC) gamma-ray observatory observes atmospheric showers produced by incident gamma rays and cosmic rays with energy from 300 GeV to more than 100 TeV. A crucial phase in analyzing gamma-ray sources using ground-based gamma-ray detectors like HAWC is to identify the showers produced by gamma rays or hadrons. The HAWC observatory records roughly 25,000 events per second, with hadrons representing the vast majority (> 99.9%) of these events. The standard gamma/hadron separation technique in HAWC uses a simple rectangular cut involving only two parameters. This work describes the implementation of more sophisticated gamma/hadron separation techniques, via machine learning methods (boosted decision trees and neural networks), and summarizes the resulting improvements in gamma/hadron separation obtained in HAWC.  
  Address [Alfaro, R.; Angeles Camacho, J. R.; Avila Rojas, D.; Belmont-Moreno, E.; Espinoza, C.; Garcia, D.; Hernandez, S.; Leon Vargas, H.; Sandoval, A.; Serna-Franco, J.] Univ Nacl Autonoma Mexico, Inst Fis, Mexico City, DF, Mexico, Email: tcapistran@astro.unam.mx;  
  Corporate Author Thesis  
  Publisher Elsevier Place of Publication Editor  
  Language English Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 0168-9002 ISBN Medium  
  Area Expedition Conference  
  Notes WOS:000861747900006 Approved no  
  Is ISI yes International Collaboration yes  
  Call Number IFIC @ pastor @ Serial 5371  
Permanent link to this record
 

 
Author Bouhova-Thacker, E.; Kostyukhin, V.; Koffas, T.; Liebig, W.; Limper, M.; Piacquadio, G.N.; Prokofiev, K.; Weiser, C.; Wildauer, A. doi  openurl
  Title (down) Expected Performance of Vertex Reconstruction in the ATLAS Experiment at the LHC Type Journal Article
  Year 2010 Publication IEEE Transactions on Nuclear Science Abbreviated Journal IEEE Trans. Nucl. Sci.  
  Volume 57 Issue 2 Pages 760-767  
  Keywords Data analysis; data reconstruction; high energy physics; pattern recognition; reconstruction algorithms; tracking; vertex detectors  
  Abstract In the harsh environment of the Large Hadron Collider at CERN (design luminosity of 10(34) cm(-2) s(-1)) efficient reconstruction of vertices is crucial for many physics analyses. Described in this paper is the expected performance of the vertex reconstruction used in the ATLAS experiment. The algorithms for the reconstruction of primary and secondary vertices as well as for finding photon conversions and vertex reconstruction in jets are described. The implementation of vertex algorithms which follows a very modular design based on object-oriented C++ is presented. A user-friendly concept allows event reconstruction and physics analyses to compare and optimize their choice among different vertex reconstruction strategies. The performance of implemented algorithms has been studied on a variety of Monte Carlo samples and results are presented.  
  Address [Bouhova-Thacker, Eva] Univ Lancaster, Lancaster LA1 4YB, England, Email: bouhova@mail.cern.ch  
  Corporate Author Thesis  
  Publisher Ieee-Inst Electrical Electronics Engineers Inc Place of Publication Editor  
  Language English Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 0018-9499 ISBN Medium  
  Area Expedition Conference  
  Notes ISI:000276679200006 Approved no  
  Is ISI yes International Collaboration yes  
  Call Number IFIC @ pastor @ Serial 260  
Permanent link to this record
 

 
Author KM3NeT Collaboration (Aiello, S. et al); Alves Garre, S.; Calvo, D.; Carretero, V.; Colomer, M.; Corredoira, I; Gozzini, S.R.; Hernandez-Rey, J.J.; Illuminati, G.; Khan Chowdhury, N.R.; Manczak, J.; Pieterse, C.; Real, D.; Salesa Greus, F.; Thakore, T.; Zornoza, J.D.; Zuñiga, J. url  doi
openurl 
  Title (down) Event reconstruction for KM3NeT/ORCA using convolutional neural networks Type Journal Article
  Year 2020 Publication Journal of Instrumentation Abbreviated Journal J. Instrum.  
  Volume 15 Issue 10 Pages P10005 - 39pp  
  Keywords Cherenkov detectors; Large detector systems for particle and astroparticle physics; Neutrino detectors; Performance of High Energy Physics Detectors  
  Abstract The KM3NeT research infrastructure is currently under construction at two locations in the Mediterranean Sea. The KM3NeT/ORCA water-Cherenkov neutrino detector off the French coast will instrument several megatons of seawater with photosensors. Its main objective is the determination of the neutrino mass ordering. This work aims at demonstrating the general applicability of deep convolutional neural networks to neutrino telescopes, using simulated datasets for the KM3NeT/ORCA detector as an example. To this end, the networks are employed to achieve reconstruction and classification tasks that constitute an alternative to the analysis pipeline presented for KM3NeT/ORCA in the KM3NeT Letter of Intent. They are used to infer event reconstruction estimates for the energy, the direction, and the interaction point of incident neutrinos. The spatial distribution of Cherenkov light generated by charged particles induced in neutrino interactions is classified as shower- or track-like, and the main background processes associated with the detection of atmospheric neutrinos are recognized. Performance comparisons to machine-learning classification and maximum-likelihood reconstruction algorithms previously developed for KM3NeT/ORCA are provided. It is shown that this application of deep convolutional neural networks to simulated datasets for a large-volume neutrino telescope yields competitive reconstruction results and performance improvements with respect to classical approaches.  
  Address [Aiello, S.; Leonora, E.; Longhitano, F.; Randazzo, N.] Ist Nazl Fis Nucl, Sez Catania, Via Santa Sofia 64, I-95123 Catania, Italy, Email: thomas.eberl@fau.de;  
  Corporate Author Thesis  
  Publisher Iop Publishing Ltd Place of Publication Editor  
  Language English Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 1748-0221 ISBN Medium  
  Area Expedition Conference  
  Notes WOS:000577278000005 Approved no  
  Is ISI yes International Collaboration yes  
  Call Number IFIC @ pastor @ Serial 4570  
Permanent link to this record
Select All    Deselect All
 |   | 
Details
   print

Save Citations:
Export Records:
ific federMinisterio de Ciencia e InnovaciĆ³nAgencia Estatal de Investigaciongva